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Quality-aware images
Z. Wang, G. Wu, H. R. Sheikh, E. P. Simoncelli, E. H. Yang, and A. C. Bovik
IEEE Transactions on Image Processing
Keywords: quality-aware image, image quality assessment, reduced-reference image quality assessment, natural image statistics, generalized Gaussian density, information hiding, image watermarking, image communication
Abstract
We propose the concept
of quality-aware image, in which certain extracted features of the
original (high-quality) image are embedded into the image data as invisible
hidden messages. When a distorted version of such an image is received, users
can decode the hidden messages and use them to provide an objective measure of
the quality of the distorted image. To demonstrate the idea, we build a
practical quality-aware image encoding, decoding and quality analysis system,
which employs 1) a novel reduced-reference image quality assessment algorithm
based on a statistical model of natural images, and 2) a previously developed
quantization watermarking-based data hiding technique in the wavelet transform
domain. A MATLAB implementation of the proposed algorithm is available online at
http://www.cns.nyu.edu/~lcv/qaware/
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